Credit Risk Manager

About Figure

Figure Technology Solutions, Inc. (Nasdaq: FIGR; OPEN: FGRS) is the leading blockchain-native capital marketplace for the origination, funding, sale and trading of tokenized assets. More than 480 partners use its loan origination system and capital marketplace. Collectively, Figure and its partners have originated over $30 billion of loans to date, among other products. The fastest growing components are Figure Connect, its credit marketplace, and Democratized Prime, Figure’s on-chain lend-borrow marketplace.

Figure’s ecosystem also includes DART (Digital Asset Registry Technology) for asset custody and lien perfection, and $YLDS, a yield-bearing stablecoin registered with the SEC as a security under the Securities Act of 1933.

Figure is the market leader in real-world asset (RWA) tokenization. The company has received triple-A ratings from S&P and Moody’s on multiple loan securitizations, the first of its kind for blockchain finance.

We’re proud to be recognized as one of Forbes’ Top 50 Fintech Companies and

CNBC’s World’s Top Fintech Companies.

About the Role

Join our team as a Credit Risk Manager! In this collaborative, high-visibility role, you will harness cutting-edge analytics and alternative data to transform customer insights into winning strategies for our HELOC and secured lending portfolios. Partnering closely with Capital Markets, Product, Engineering, Servicing, and Compliance, you will oversee credit policies, guide execution, and pioneer creative risk frameworks that safeguard portfolio health while unlocking growth.

If you are a proactive problem solver who loves digging deep into lending analytics, exploring novel data sources, and uniting cross-functional teams around portfolio performance, we want to hear from you.

What You’ll Do

• Continuously refine and modernize credit underwriting strategies using advanced analytics to optimize risk decisions across lending products.
• Analyze historical loan performance data to model credit expansion initiatives, identify new customer segments, and optimize funnel conversion.
• Perform root-cause analyses on credit losses and default trends, partnering with Fraud Risk Management to sharpen fraud controls.
• Develop valuation models to estimate segment-level economics and advise Capital Markets on yield projections and performance assumptions.
• Partner with Product, Engineering, and Data Science to design A/B tests that balance risk control, conversion lift, and user experience.
• Track and validate pre- and post-implementation performance for all deployed credit and fraud rule changes.
• Design monitoring frameworks to track new product launches at a granular segment level, identify emerging portfolio risks, and inform executive decision-making.
• Present Figure’s underwriting methodology to investors and serve as a core contact for due diligence and portfolio performance inquiries.
• Collaborate with Legal and Compliance to ensure all credit strategies strictly meet regulatory requirements.
• Conduct ad hoc quantitative analyses to support broader Credit, Operations, and Product objectives.

What We Look For

• Bachelor/Master’s degree with a quantitative background (e.g., Statistics, Math, Economics, Computer Science, Engineering, or Business).
• 5+ years in credit risk management or data science within consumer lending.
• Comfortable working in a fast-moving, evolving environment where priorities shift, and initiatives move quickly.
• Self-driven, with intense focus on results. High curiosity with a proven track record of probing root causes, challenging the status quo, and designing out-of-the-box solutions.
• Strong analytical and problem-solving skills, combined with solid business judgment
• Clear, strong communicator who can translate complex data into simple, actionable insights for any audience.
• Strong team player and comfortable interacting with partners across multiple teams and at varying levels of seniority
• Advanced proficiency in SQL and Python/R for pulling, cleaning, and modeling complex relational data independently.
• Practical application of predictive modeling, customer segmentation, and statistical procedures to evaluate risk and borrower behavior.
• Experience with Tableau, Power BI, and Looker.
• Adhere to all company security policies and data handling procedures.
• Complete mandatory security awareness training within required timeframes.
• Promptly report any suspected security incidents or suspicious activity to the Security team.